Search and detection of epitopes in Trans-sialidases protein family from Trypanosoma cruzi

BOURDIN ED; LEIVA MJP; BONTEMPI I; MARCIPAR I; AMADIO AF

Rosario

Congreso; 4to Congreso Argentino de Bioinformática; 2013

Asociación Argentina de Bioinformática

Preliminary studies on murine models, showed evidences that fragments of the Trans-sialidase proteins (TS) give the best inmunoprotection against Chagas disease[1]. Trans-sialidases constitutes a super family of proteins, highly variable, present on the surface of Trypanosoma cruzi, the etiologic agent of Chagas disease. Epitopes are considered the portion of a macromolecule that is recognized by the immune system. The objective of this study was to select a set of Major Histocompatibility Complex (MHC class I y classII) restricted T-epitopes able to generate an adequate immune response against the pathogen. Generally, conserved regions are used for searching epitopes in a protein family, however, this was impossible in TS due to the high heterogeneity of these proteins. In this way, we proposed to select a number of epitopes that were present in a highly variable family of proteins, not by searching for conserved regions, but by the exploitation of its diversity. A dataset containing 1597 reliable sequences corresponding to TS was available as a result of previous work of our group. Epitopes from MHC class I were predicted for each sequence in the dataset using NETMHCI [2]. Predicted epitopes were of 10, 11 and 12 aminoacids in length and were recognized by human alleles: A*0101, A*0201, A*0301, A*2402, B*0702 and B*4403, potentially covering binding properties over 99% of know human MHCI [3]. For the prediction of epitopes belonging to MHC class II, the same dataset of TS was processed with NETMHCII [4]. Predicted epitopes were of 15 aminoacids in length, and were recognized by human alleles: DRB1*0101, DRB1*0301, DRB1*0401, DRB1*0701, DRB1*1101 y DRB1*1501, which cover approximately 95% of human populations [5]. The predictions made generated a considerable amount of results. To remove irrelevant results, only best candidates were selected. This was done by filtering the results based on the strength of interaction, up to 50mM were considered a strong interaction, and those having strength between 50 and 500 nM were considered a weak interaction. Finally, a combination of epitopes were selected based on three conditions; i) whenthey show reaction with the highest possible number of MHC alleles; ii) when the interaction force was high; and finally iii) when epitopes were present in the highest number of sequences in the dataset (ie, the coverage of sequences must be high). To solve this optimization problem, a genetic algorithm approach was followed. Conclusion The filter and selection strategy used, yielded a potential combination of 20 epitopes that together covered 84% of the sequences in the considered dataset, and were recognized by MHC class I molecules. For MHC class II, the 20 epitopes selected, covered 73% of the sequences in the considered dataset. The total set of epitopes obtained should be able to generate an immune response for most local human populations given its wide range of MHC allele coverage.