Immunoinformatic epitope prediction for immune response, escape and adverse events modelling in the preclinical development of vaccines and therapeutical recombinant proteins.
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1
Las Tunas General Teaching Hospital, Molecular Medicine Unit, Cuba
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2
Center of Toxicology and Biomedicine, Laboratory of Immunotoxicology, Cuba
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3
Institute of Basic and Preclinical Sciences, Immunology Department, Cuba
Background: Immunoinformatic databases and tools have been designed in the last years to computationally model different events of the immune response. Antigen presentation, proteasomal cleavage and related processes have received particular attention due to their central role in immune responses against pathogens and the knowledge accumulated so far about their molecular basis. Immunoinformatics is being integrated into the development of vaccine candidates and recombinant proteins obtained from infectious agents. Concerning the latter, bioinformatic tools could be of aid both in the selection of the best targets, in terms of protection, and in the prediction of adverse events even before its assessment in animal models. By integrating technologies and expertise from diverse fields and by optimising the development process of new products, bioinformatics should be taken into account by research groups from middle and low income countries.
Methods: In order to compare murine and human immune responses and to select the most immunogenic epitopes, two widely used pathogen-derived proteins were selected as model targets: recombinant streptokinase (UniProt Q53284) and hepatitis B surface antigen (GenBank X02763.1). Both B- and T-cell responses were modelled by immunoinformatic tools: BepiPred, Bcepred and ABCpred for antibody responses; SYFPEITHI and BIMAS for cellular responses in the context of H2-Kd, H2-Kk, HLA-A*0201, HLA-DRB1*0301 and HLA-DRB1*0701. With the objective of finding potential deleterious, vaccine-related cross-reactive and/or autoimmune responses against prophylactic vaccines, top nonamers, as predicted from the primary sequence of HBsAg using SYFPEITHI, were used to find similar peptides in human proteins sharing at least 75% similarity, with FastA algorithm, proteome database, Homo sapiens dataset and fasta3 program. Only proteins from the central nervous system were considered, taking into account the recent debate on the association between hepatitis B vaccine and multiple sclerosis. By Sequence Retrieval System from European Bioinformatics Institute, 25 primary sequences of HBsAg were selected and compared by ClustalW, in order to find variations in immunodominant epitopes as predicted by SYFPEITHI.
Results: In the case of streptokinase, a number of epitopes, already reported by in vitro studies, were also found by immunoinfomatic algorithms: 379-390, 397-410, 139-152 and 296-310, among others. Overlapping murine and human responses were found for HLA-A*0201 and H2-Kk in the positions 133/135, 259/262/268/269 and for class II HLA and H2-Kk in the regions 98/101, 226/232 and 343/346. For HbsAg, five matches (45/50, 185/194, 191/194, 199/194, 267/272) were reported for class II HLA and H2-Kk, while only two for HLA-A*0201 and H2-Kk (191, 264/272).
Only one human protein had a similarity above cutoff value with the HbsAg nonamer LLLCLIFLL, a Striatum G-protein couple receptor. There is no relationship between this molecule and multiple sclerosis or any other human condition, thus there must be strict immune mechanisms to control autoimmune response against this target in vivo. However, since other 24 human proteins from other tissues and organs showed similarities of more than 75% with nonamers derived from HbsAg, the methodology could be of value for both adverse event prediction and to direct post-marketing surveillance of vaccines and recombinant proteins.
Sequence variations in HbsAg ranged from 2 to 29 residues. The nonamer LLLCLIFLL, which ranked first in 11 entries, was second in other nine sequences and third in the other five HbsAg selected. Antigenic variation among circulating strains of viral and bacterial pathogens could thus be considered as a cause of vaccine failure, and bioinformatic tools could help to predict it and correct it by the design of multiepitopic candidates.
Conclusions: Immunoinformatic tools are useful to predict pathogen-derived epitopes to be included in vaccines, to preclinically assess potential autoimmune responses to recombinant proteins and to compare murine and human immune responses. Bioinformatics is also essential in the study of molecular evolution of pathogens, their patterns of circulation and the prediction of vaccine failure and the emergence of antimicrobial resistance.
Keywords:
Computational Biology,
immunoinformatics,
epitope prediction,
Vaccinomics,
Sequence variation,
Escape variants,
adverse events
Conference:
IMMUNOCOLOMBIA2015 - 11th Congress of the Latin American Association of Immunology - 10o. Congreso de la Asociación Colombiana de Alergia, Asma e Inmunología, Medellin, Colombia, 13 Oct - 16 Oct, 2015.
Presentation Type:
Poster Presentation
Topic:
Adaptive Immunity
Citation:
Serrano-Barrera
OR,
Batista-Duharte
A and
Pérez-Martin
OG
(2015). Immunoinformatic epitope prediction for immune response, escape and adverse events modelling in the preclinical development of vaccines and therapeutical recombinant proteins..
Front. Immunol.
Conference Abstract:
IMMUNOCOLOMBIA2015 - 11th Congress of the Latin American Association of Immunology - 10o. Congreso de la Asociación Colombiana de Alergia, Asma e Inmunología.
doi: 10.3389/conf.fimmu.2015.05.00039
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Received:
07 Apr 2015;
Published Online:
14 Sep 2015.
*
Correspondence:
Dr. Orlando R Serrano-Barrera, Las Tunas General Teaching Hospital, Molecular Medicine Unit, Las Tunas, Las Tunas, 75100, Cuba, orlandosb@infomed.sld.cu