De la secuencia de un genoma bacteriano a la identificación de candidatos vacunales.

Identifying Vaccine Candidates from the Sequence of a Bacterial Genome.

Daniel Yero Corona.

Instituto Finlay. Centro de Investigación-Producción de Vacunas. Ave. 27 No. 19805. La Lisa. A.P. 16017, C.P. 11600. Ciudad de La Habana, Cuba. E-mail: dyero@finlay.edu.cu

RESUMEN

Cada día hay más secuencias genómicas completas de un gran número de patógenos humanos. La disponibilidad de estas secuencias ha cambiado completamente el panorama para el desarrollo de vacunas, introduciendo una nueva línea de pensamiento en este proceso. Esta metodología comienza por la secuencia genómica y mediante un análisis computacional se predicen aquellos antígenos más probables a ser candidatos vacunales. Por ejemplo, con el uso de herramientas bioinformáticas se puede hacer un pesquisaje in silico de aquellas proteínas expuestas en la superficie bacteriana, con vistas a identificar antígenos candidatos vacunales. La confirmación in vitro de estos resultados de localización celular y el uso de modelos animales para evaluar la inmunogenicidad de los candidatos acota finalmente el número de candidatos definidos por la computadora. A este proceso, aplicado por primera vez a Neisseria meningitidis serogrupo B, se le denomina vacunología inversa. La genómica también brinda información sobre la biología y la virulencia de especies patogénicas mediante la genómica comparativa. En este trabajo de revisión, describimos cómo la genómica puede ser usada en la identificación de nuevos candidatos vacunales.

ABSTRACT

Whole genome sequence data are increasingly available for a wide range of human pathogens. The availability of these sequences has changed our approach to vaccine development entirely and introduced a new way of thinking in this process. This approach starts from the genomic sequence and, by computer analysis, predicts those antigens that are most likely to be vaccine candidates. The use of bioinformatic tools allows the comprehensive in silico screening of genome data for surface-expressed proteins, in order to identify candidate vaccine antigens. In vitro confirmation of surface location and the use of animal models to test immunogenicity further refine the list of proteins likely to be of use as vaccine antigens. This process, first applied to serogroup B Neisseria meningitidis, has been termed as reverse vaccinology. Genomics also
enables valuable information concerning the biology and virulence of the pathogenic species to be extracted by comparative genomics. In this review, we describe how genomic approaches can be used to identify novel vaccine candidates.

Keywords: Genomics, Vaccines, Bioinformatics, Reverse Vaccinology, Neisseria meningitidis.

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