De Brito Rory Cristiane Fortes, Cardoso Jamille Mirelle de Oliveira, Reis Levi Eduardo Soares, Mathias Fernando Augusto Siqueira, Aguiar-Soares Rodrigo Dian de Oliveira, Teixeira-Carvalho Andréa, Roatt Bruno Mendes, Corrêa-Oliveira Rodrigo, Ruiz Jeronimo Conceição, Resende Daniela de Melo, Reis Alexandre Barbosa
Laboratório de Imunopatologia, Núcleo de Pesquisas em Ciências Biológicas/NUPEB, Universidade Federal de Ouro Preto, 35400-00 Ouro Preto, Minas Gerais, Brazil.
Laboratório Multiusuário de Citometria de Fluxo, Núcleo de Pesquisas em Ciências Biológicas/NUPEB, Universidade Federal de Ouro Preto, 35400-00 Ouro Preto, Minas Gerais, Brazil.
Vaccines (Basel). 2019 Oct 28;7(4):162. doi: 10.3390/vaccines7040162.
Reverse vaccinology or immunoinformatics is a computational methodology which integrates data from in silico epitope prediction, associated to other important information as, for example, the predicted subcellular location of the proteins used in the design of the context of vaccine development. This approach has the potential to search for new targets for vaccine development in the predicted proteome of pathogenic organisms. To date, there is no effective vaccine employed in vaccination campaigns against visceral leishmaniasis (VL). For the first time, herein, an in silico, in vitro, and in vivo peptide screening was performed, and immunogenic peptides were selected to constitute VL peptide-based vaccines. Firstly, the screening of in silico potential peptides using dogs naturally infected by was conducted and the peptides with the best performance were selected. The mentioned peptides were used to compose Cockt-1 (cocktail 1) and Cockt-2 (cocktail 2) in combination with saponin as the adjuvant. Therefore, tests for immunogenicity, polyfunctional T-cells, and the ability to induce central and effector memory in T-lymphocytes capacity in reducing the parasite load on the spleen for Cockt-1 and Cockt-2 were performed. Among the vaccines under study, Cockt-1 showed the best results, eliciting CD4 and CD8 polyfunctional T-cells, with a reduction in spleen parasitism that correlates to the generation of T CD4 central memory and T CD8 effector memory cells. In this way, our findings corroborate the use of immunoinformatics as a tool for the development of future vaccines against VL.
反向疫苗学或免疫信息学是一种计算方法，它整合了来自计算机模拟表位预测的数据，并与其他重要信息相关联，例如在疫苗开发背景下设计中所使用蛋白质的预测亚细胞定位。这种方法有潜力在致病生物体的预测蛋白质组中寻找疫苗开发的新靶点。迄今为止，在针对内脏利什曼病（VL）的疫苗接种运动中尚未使用有效的疫苗。在此，首次进行了计算机模拟、体外和体内肽筛选，并选择了免疫原性肽来构成基于VL肽的疫苗。首先，对自然感染的犬进行了计算机模拟潜在肽的筛选，并选择了性能最佳的肽。上述肽与皂苷作为佐剂组合用于组成Cockt-1（鸡尾酒1）和Cockt-2（鸡尾酒2）。因此，对Cockt-1和Cockt-2进行了免疫原性、多功能T细胞以及诱导T淋巴细胞中中央记忆和效应记忆能力以降低脾脏寄生虫负荷的测试。在所研究的疫苗中，Cockt-1显示出最佳结果，引发了CD4和CD8多功能T细胞，脾脏寄生虫感染减少，这与T CD4中央记忆和T CD8效应记忆细胞的产生相关。通过这种方式，我们的研究结果证实了免疫信息学作为开发未来抗VL疫苗工具的用途。
