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Leishmania spp Epitopes in Humans Naturally Resistant to the Disease: Working Toward a Synthetic Vaccine.

ABSTRACT: Vaccines are one of the most effective strategies to fight infectious diseases. Reverse vaccinology strategies provide tools to perform in silico screening and a rational selection of potential candidates on a large scale before reaching in vitro and in vivo evaluations. Leishmania infection in humans produces clinical symptoms in some individuals, while another part of the population is naturally resistant (asymptomatic course) to the disease, and therefore their immune response controls parasite replication. By the identification of epitopes directly in humans, especially in those resistant to the disease, the probabilities of designing an effective vaccine are higher. The aim of this work was the identification of Leishmania epitopes in resistant humans. To achieve that, 11 peptide sequences (from Leishmania antigenic proteins) were selected using epitope prediction tools, and then, peripheral blood mononuclear cells (PBMCs) were isolated from human volunteers who were previously divided into four clinical groups: susceptible, resistant, exposed and not exposed to the parasite. The induction of inflammatory cytokines and lymphoproliferation was assessed using monocyte-derived dendritic cells (moDCs) as antigen-presenting cells (APCs). The response was evaluated after exposing volunteers' cells to each peptide. As a result, we learned that STI41 and STI46 peptides induced IL-8 and IL-12 in moDCs and lymphoproliferation and low levels of IL-10 in lymphocytes differentially in resistant volunteers, similar behavior to that observed in those individuals to L. panamensis lysate antigens. We conclude that, in silico analysis allowed for the identification of natural Leishmania epitopes in humans, and also STI41 and STI46 peptides could be epitopes that lead to a cellular immune response directed at parasite control.

SUBMITTER: Florez MM

PROVIDER: S-EPMC8216392 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:A number of machine learning-based predictors have been developed for identifying immunogenic T-cell epitopes based on major histocompatibility complex (MHC) class I and II binding affinities. Rationally selecting the most appropriate tool has been complicated by the evolving training data and machine learning methods. Despite the recent advances made in generating high-quality MHC-eluted, naturally processed ligandome, the reliability of new predictors on these epitopes has yet to be evaluated. This study reports the latest benchmarking on an extensive set of MHC-binding predictors by using newly available, untested data of both synthetic and naturally processed epitopes. 32 human leukocyte antigen (HLA) class I and 24 HLA class II alleles are included in the blind test set. Artificial neural network (ANN)-based approaches demonstrated better performance than regression-based machine learning and structural modeling. Among the 18 predictors benchmarked, ANN-based mhcflurry and nn_align perform the best for MHC class I 9-mer and class II 15-mer predictions, respectively, on binding/non-binding classification (Area Under Curves = 0.911). NetMHCpan4 also demonstrated comparable predictive power. Our customization of mhcflurry to a pan-HLA predictor has achieved similar accuracy to NetMHCpan. The overall accuracy of these methods are comparable between 9-mer and 10-mer testing data. However, the top methods deliver low correlations between the predicted versus the experimental affinities for strong MHC binders. When used on naturally processed MHC-ligands, tools that have been trained on elution data (NetMHCpan4 and MixMHCpred) shows better accuracy than pure binding affinity predictor. The variability of false prediction rate is considerable among HLA types and datasets. Finally, structure-based predictor of Rosetta FlexPepDock is less optimal compared to the machine learning approaches. With our benchmarking of MHC-binding and MHC-elution predictors using a comprehensive metrics, a unbiased view for establishing best practice of T-cell epitope predictions is presented, facilitating future development of methods in immunogenomics.

Project description:Leishmaniasis is a spectrum of diseases transmitted by sand fly vectors that deposit Leishmania spp. parasites in the host skin during blood feeding. Currently, available treatment options are limited, associated with high toxicity and emerging resistance. Even though a vaccine for human leishmaniasis is considered an achievable goal, to date we still do not have one available, a consequence (amongst other factors) of a lack of pre-clinical to clinical translatability. Pre-exposure to uninfected sand fly bites or immunization with defined sand fly salivary proteins was shown to negatively impact infection. Still, cross-protection reports are rare and dependent on the phylogenetic proximity of the sand fly species, meaning that the applicability of a sand fly saliva-based vaccine will be limited to a defined geography, one parasite species and one form of leishmaniasis. As a proof of principle of a future vector saliva-based pan-Leishmania vaccine, we engineered through a reverse vaccinology approach that maximizes translation to humans, a fusion protein consisting of immunogenic portions of PdSP15 and LJL143, sand fly salivary proteins demonstrated as potential vaccine candidates against cutaneous and visceral leishmaniasis, respectively. The in silico analysis was validated ex vivo, through T cell proliferation experiments, proving that the fusion protein (administered as a DNA vaccine) maintained the immunogenicity of both PdSP15 and LJL143. Additionally, while no significant effect was detected in the context of L. major transmission by P. duboscqi, this DNA vaccine was defined as partially protective, in the context of L. major transmission by L. longipalpis sand flies. Importantly, a high IFNγ response alone was not enough to confer protection, that mainly correlated with low T cell mediated Leishmania-specific IL-4 and IL-10 responses, and consequently with high pro/anti-inflammatory cytokine ratios. Overall our immunogenicity data suggests that to design a potentially safe vector-based pan-Leishmania vaccine, without geographic restrictions and against all forms of leishmaniasis is an achievable goal. This is why we propose our approach as a proof-of principle, perhaps not only applicable to the anti-Leishmania vector-based vaccines' field, but also to other branches of knowledge that require the design of multi-epitope T cell vaccines with a higher potential for translation.

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Leishmania spp Epitopes in Humans Naturally Resistant to the Disease: Working Toward a Synthetic Vaccine.

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