免疫信息学与蜱疫苗学

R. Rosario-Cruz, D. Domínguez-García, Saúl López-Silva, Fernando Rosario-Domínguez
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摘要

免疫信息学是一个新兴领域,侧重于开发和应用用于促进疫苗开发的方法。人们对以名为“疫苗组学”的新基因组学为中心的疫苗学领域的兴趣日益浓厚。然而,这种方法还没有成功地提供一种针对影响动物和人类的重大感染的解决方案,因为蜱疫苗仍在基于传统的生化或免疫学方法开发,以解剖病原体的分子结构,寻找候选抗原。全基因组的可用性和新的先进技术,如数据挖掘、生物信息学、微阵列和蛋白质组学,已经彻底改变了疫苗开发的方法,并为蜱虫研究提供了新的动力。本综述的目的是探讨现代疫苗学如何有助于发现新的候选抗原,并了解改进现有疫苗的研究过程。根据这一概念,蜱虫的组学年龄将使设计疫苗成为可能,这一预测是基于计算机算法通过数据挖掘获得的基因序列的计算机分析,而无需让病原体在体外生长。这种新的基于基因组的方法被命名为“反向疫苗学3.0”或“疫苗组学1.0”,可以应用于蜱虫。
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Immunoinformatics and tick vaccinology
Immunoinformatics is an emerging area focused on development and applications of methods used to facilitate vaccine development. There is a growing interest in the field of vaccinology centered on the new omic science named ‘vaccinomics’. However, this approach has not succeeded to provide a solution against major infections affecting both animals and humans, since tick vaccines are still being developed based on conventional biochemical or immunological methods to dissect the molecular structure of the pathogen, looking for a candidate antigen. The availability of complete genomes and the novel advanced technologies, such as data mining, bioinformatics, microarrays, and proteomics, have revolutionized the approach to vaccine development and provided a new impulse to tick research. The aim of this review is to explore how modern vaccinology will contribute to the discovery of new candidate antigens and to understand the research process to improve existing vaccines. Under this concept, the omic age of ticks will make it possible to design vaccines starting from a prediction based on the in silico analysis of gene sequences obtained by data mining using computer algorithms, without the need to keep the pathogen growing in vitro. This new genome-based approach has been named “reverse vaccinology 3.0” or “vaccinomics 1.0” and can be applied to ticks.
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