TY - JOUR
T1 - Identification of novel potential vaccine candidates against tuberculosis based on reverse vaccinology
AU - Monterrubio-López, Gloria P.
AU - González-Y-Merchand, Jorge A.
AU - Ribas-Aparicio, Rosa Mariá
N1 - Publisher Copyright:
© 2015 Gloria P. Monterrubio-López et al.
PY - 2015
Y1 - 2015
N2 - Tuberculosis (TB) is a chronic infectious disease, considered as the second leading cause of death worldwide, caused by Mycobacterium tuberculosis. The limited efficacy of the bacillus Calmette-Guérin (BCG) vaccine against pulmonary TB and the emergence of multidrug-resistant TB warrants the need for more efficacious vaccines. Reverse vaccinology uses the entire proteome of a pathogen to select the best vaccine antigens by in silico approaches. M. tuberculosis H37Rv proteome was analyzed with NERVE (New Enhanced Reverse Vaccinology Environment) prediction software to identify potential vaccine targets; these 331 proteins were further analyzed with VaxiJen for the determination of their antigenicity value. Only candidates with values ≥0.5 of antigenicity and 50% of adhesin probability and without homology with human proteins or transmembrane regions were selected, resulting in 73 antigens. These proteins were grouped by families in seven groups and analyzed by amino acid sequence alignments, selecting 16 representative proteins. For each candidate, a search of the literature and protein analysis with different bioinformatics tools, as well as a simulation of the immune response, was conducted. Finally, we selected six novel vaccine candidates, EsxL, PE26, PPE65, PE-PGRS49, PBP1, and Erp, from M. tuberculosis that can be used to improve or design new TB vaccines.
AB - Tuberculosis (TB) is a chronic infectious disease, considered as the second leading cause of death worldwide, caused by Mycobacterium tuberculosis. The limited efficacy of the bacillus Calmette-Guérin (BCG) vaccine against pulmonary TB and the emergence of multidrug-resistant TB warrants the need for more efficacious vaccines. Reverse vaccinology uses the entire proteome of a pathogen to select the best vaccine antigens by in silico approaches. M. tuberculosis H37Rv proteome was analyzed with NERVE (New Enhanced Reverse Vaccinology Environment) prediction software to identify potential vaccine targets; these 331 proteins were further analyzed with VaxiJen for the determination of their antigenicity value. Only candidates with values ≥0.5 of antigenicity and 50% of adhesin probability and without homology with human proteins or transmembrane regions were selected, resulting in 73 antigens. These proteins were grouped by families in seven groups and analyzed by amino acid sequence alignments, selecting 16 representative proteins. For each candidate, a search of the literature and protein analysis with different bioinformatics tools, as well as a simulation of the immune response, was conducted. Finally, we selected six novel vaccine candidates, EsxL, PE26, PPE65, PE-PGRS49, PBP1, and Erp, from M. tuberculosis that can be used to improve or design new TB vaccines.
UR - http://www.scopus.com/inward/record.url?scp=84928797204&partnerID=8YFLogxK
U2 - 10.1155/2015/483150
DO - 10.1155/2015/483150
M3 - Artículo
C2 - 25961021
SN - 2314-6133
VL - 2015
JO - BioMed Research International
JF - BioMed Research International
M1 - 483150
ER -