Integrated computational and experimental workflow identifies a novel T-cell epitope from Babesia bovis RON5 recognized by infected cattle

Autores
Valenzano, Magali Nicole; Montenegro, Valeria Noely; Paoletta, Martina; Gravisaco, María José; Valentini, Beatriz Susana; Guillemi, Eliana Carolina; Alvarez, Liliana; Nielsen, Morten Munch B.; Wilkowsky, Silvina Elizabeth
Año de publicación
2026
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Babesia bovis is a tick-borne apicomplexan parasite that causes bovine babesiosis, a disease of major economic importance in cattle worldwide. The development of effective subunit vaccines against Babesia bovis requires the identification of T-cell epitopes capable of inducing protective cellular immune responses. This task remains challenging due to the limited characterization of binding specificity of bovine leukocyte antigen class II molecules, which are essential for accurate epitope prediction, as well as the scarce information available on the antigenic repertoire of B. bovis. Moreover, computational approaches must be complemented with experimental validation to confirm the immunogenicity of the predicted epitopes. In this study, we developed an integrated computational and experimental workflow to identify potential novel T-cell epitopes from a subset of B. bovis secreted proteins. Using a tailored epitope prediction algorithm based on the genome sequence of a pathogenic strain combined with available transcriptomic data, we identified and experimentally validated two peptides on their capacity to induce the release of IFN- γ by T CD4+ cells: one that overlaps with a previously reported epitope from the Rhoptry-Associated Protein 1 and a novel epitope derived from the Rhoptry Neck Protein 5. Our approach highlights the power of combining in silico prediction with in vitro validation to discover candidate antigens that may contribute to the development of effective vaccines or immunotherapies for bovine babesiosis.
Instituto de Biotecnología
Fil: Valenzano, Magali Nicole. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Valenzano, Magali Nicole. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Montenegro, Valeria Noely. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Montenegro, Valeria Noely. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Paoletta, Martina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Paoletta, Martina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Gravisaco, Marí­a José. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Gravisaco, Marí­a José. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Valentini, Beatriz Susana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; Argentina
Fil: Guillemi, Eliana Carolina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Guillemi, Eliana Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Alvarez, Liliana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Alvarez, Liliana. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Nielsen, Morten Munch B. Technical University of Denmark. Department of Health Technology; Dinamarca
Fil: Wilkowsky, Silvina Elizabeth. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Wilkowsky, Silvina Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fuente
Vaccine 72 : 128081. (February 2026)
Materia
Ganado Bovino
Enfermedades de los Animales
Respuesta Inmunológica
Interferonas
Linfocitos-t
Cattle
Animal Diseases
Babesia bovis
Babesiosis
Immune Response
Interferons
T-lymphocytes
Interferon Gamma
Células-t
T-cell
Nivel de accesibilidad
acceso restringido
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/25222
Acceder
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oai_identifier_str oai:localhost:20.500.12123/25222
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling Integrated computational and experimental workflow identifies a novel T-cell epitope from Babesia bovis RON5 recognized by infected cattleValenzano, Magali NicoleMontenegro, Valeria NoelyPaoletta, MartinaGravisaco, María JoséValentini, Beatriz SusanaGuillemi, Eliana CarolinaAlvarez, LilianaNielsen, Morten Munch B.Wilkowsky, Silvina ElizabethGanado BovinoEnfermedades de los AnimalesRespuesta InmunológicaInterferonasLinfocitos-tCattleAnimal DiseasesBabesia bovisBabesiosisImmune ResponseInterferonsT-lymphocytesInterferon GammaCélulas-tT-cellBabesia bovis is a tick-borne apicomplexan parasite that causes bovine babesiosis, a disease of major economic importance in cattle worldwide. The development of effective subunit vaccines against Babesia bovis requires the identification of T-cell epitopes capable of inducing protective cellular immune responses. This task remains challenging due to the limited characterization of binding specificity of bovine leukocyte antigen class II molecules, which are essential for accurate epitope prediction, as well as the scarce information available on the antigenic repertoire of B. bovis. Moreover, computational approaches must be complemented with experimental validation to confirm the immunogenicity of the predicted epitopes. In this study, we developed an integrated computational and experimental workflow to identify potential novel T-cell epitopes from a subset of B. bovis secreted proteins. Using a tailored epitope prediction algorithm based on the genome sequence of a pathogenic strain combined with available transcriptomic data, we identified and experimentally validated two peptides on their capacity to induce the release of IFN- γ by T CD4+ cells: one that overlaps with a previously reported epitope from the Rhoptry-Associated Protein 1 and a novel epitope derived from the Rhoptry Neck Protein 5. Our approach highlights the power of combining in silico prediction with in vitro validation to discover candidate antigens that may contribute to the development of effective vaccines or immunotherapies for bovine babesiosis.Instituto de BiotecnologíaFil: Valenzano, Magali Nicole. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Valenzano, Magali Nicole. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Montenegro, Valeria Noely. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Montenegro, Valeria Noely. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Paoletta, Martina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Paoletta, Martina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gravisaco, Marí­a José. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Gravisaco, Marí­a José. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Valentini, Beatriz Susana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; ArgentinaFil: Guillemi, Eliana Carolina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Guillemi, Eliana Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Alvarez, Liliana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Alvarez, Liliana. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Nielsen, Morten Munch B. Technical University of Denmark. Department of Health Technology; DinamarcaFil: Wilkowsky, Silvina Elizabeth. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Wilkowsky, Silvina Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaElsevier2026-02-18T14:26:51Z2026-02-18T14:26:51Z2026-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/25222https://www.sciencedirect.com/science/article/abs/pii/S0264410X250137990264-410X1873-2518https://doi.org/10.1016/j.vaccine.2025.128081Vaccine 72 : 128081. (February 2026)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2026-02-26T11:47:42Zoai:localhost:20.500.12123/25222instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2026-02-26 11:47:42.726INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Integrated computational and experimental workflow identifies a novel T-cell epitope from Babesia bovis RON5 recognized by infected cattle
title Integrated computational and experimental workflow identifies a novel T-cell epitope from Babesia bovis RON5 recognized by infected cattle
spellingShingle Integrated computational and experimental workflow identifies a novel T-cell epitope from Babesia bovis RON5 recognized by infected cattle
Valenzano, Magali Nicole
Ganado Bovino
Enfermedades de los Animales
Respuesta Inmunológica
Interferonas
Linfocitos-t
Cattle
Animal Diseases
Babesia bovis
Babesiosis
Immune Response
Interferons
T-lymphocytes
Interferon Gamma
Células-t
T-cell
title_short Integrated computational and experimental workflow identifies a novel T-cell epitope from Babesia bovis RON5 recognized by infected cattle
title_full Integrated computational and experimental workflow identifies a novel T-cell epitope from Babesia bovis RON5 recognized by infected cattle
title_fullStr Integrated computational and experimental workflow identifies a novel T-cell epitope from Babesia bovis RON5 recognized by infected cattle
title_full_unstemmed Integrated computational and experimental workflow identifies a novel T-cell epitope from Babesia bovis RON5 recognized by infected cattle
title_sort Integrated computational and experimental workflow identifies a novel T-cell epitope from Babesia bovis RON5 recognized by infected cattle
dc.creator.none.fl_str_mv Valenzano, Magali Nicole
Montenegro, Valeria Noely
Paoletta, Martina
Gravisaco, María José
Valentini, Beatriz Susana
Guillemi, Eliana Carolina
Alvarez, Liliana
Nielsen, Morten Munch B.
Wilkowsky, Silvina Elizabeth
author Valenzano, Magali Nicole
author_facet Valenzano, Magali Nicole
Montenegro, Valeria Noely
Paoletta, Martina
Gravisaco, María José
Valentini, Beatriz Susana
Guillemi, Eliana Carolina
Alvarez, Liliana
Nielsen, Morten Munch B.
Wilkowsky, Silvina Elizabeth
author_role author
author2 Montenegro, Valeria Noely
Paoletta, Martina
Gravisaco, María José
Valentini, Beatriz Susana
Guillemi, Eliana Carolina
Alvarez, Liliana
Nielsen, Morten Munch B.
Wilkowsky, Silvina Elizabeth
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Ganado Bovino
Enfermedades de los Animales
Respuesta Inmunológica
Interferonas
Linfocitos-t
Cattle
Animal Diseases
Babesia bovis
Babesiosis
Immune Response
Interferons
T-lymphocytes
Interferon Gamma
Células-t
T-cell
topic Ganado Bovino
Enfermedades de los Animales
Respuesta Inmunológica
Interferonas
Linfocitos-t
Cattle
Animal Diseases
Babesia bovis
Babesiosis
Immune Response
Interferons
T-lymphocytes
Interferon Gamma
Células-t
T-cell
dc.description.none.fl_txt_mv Babesia bovis is a tick-borne apicomplexan parasite that causes bovine babesiosis, a disease of major economic importance in cattle worldwide. The development of effective subunit vaccines against Babesia bovis requires the identification of T-cell epitopes capable of inducing protective cellular immune responses. This task remains challenging due to the limited characterization of binding specificity of bovine leukocyte antigen class II molecules, which are essential for accurate epitope prediction, as well as the scarce information available on the antigenic repertoire of B. bovis. Moreover, computational approaches must be complemented with experimental validation to confirm the immunogenicity of the predicted epitopes. In this study, we developed an integrated computational and experimental workflow to identify potential novel T-cell epitopes from a subset of B. bovis secreted proteins. Using a tailored epitope prediction algorithm based on the genome sequence of a pathogenic strain combined with available transcriptomic data, we identified and experimentally validated two peptides on their capacity to induce the release of IFN- γ by T CD4+ cells: one that overlaps with a previously reported epitope from the Rhoptry-Associated Protein 1 and a novel epitope derived from the Rhoptry Neck Protein 5. Our approach highlights the power of combining in silico prediction with in vitro validation to discover candidate antigens that may contribute to the development of effective vaccines or immunotherapies for bovine babesiosis.
Instituto de Biotecnología
Fil: Valenzano, Magali Nicole. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Valenzano, Magali Nicole. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Montenegro, Valeria Noely. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Montenegro, Valeria Noely. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Paoletta, Martina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Paoletta, Martina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Gravisaco, Marí­a José. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Gravisaco, Marí­a José. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Valentini, Beatriz Susana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; Argentina
Fil: Guillemi, Eliana Carolina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Guillemi, Eliana Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Alvarez, Liliana. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Alvarez, Liliana. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Nielsen, Morten Munch B. Technical University of Denmark. Department of Health Technology; Dinamarca
Fil: Wilkowsky, Silvina Elizabeth. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; Argentina
Fil: Wilkowsky, Silvina Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Babesia bovis is a tick-borne apicomplexan parasite that causes bovine babesiosis, a disease of major economic importance in cattle worldwide. The development of effective subunit vaccines against Babesia bovis requires the identification of T-cell epitopes capable of inducing protective cellular immune responses. This task remains challenging due to the limited characterization of binding specificity of bovine leukocyte antigen class II molecules, which are essential for accurate epitope prediction, as well as the scarce information available on the antigenic repertoire of B. bovis. Moreover, computational approaches must be complemented with experimental validation to confirm the immunogenicity of the predicted epitopes. In this study, we developed an integrated computational and experimental workflow to identify potential novel T-cell epitopes from a subset of B. bovis secreted proteins. Using a tailored epitope prediction algorithm based on the genome sequence of a pathogenic strain combined with available transcriptomic data, we identified and experimentally validated two peptides on their capacity to induce the release of IFN- γ by T CD4+ cells: one that overlaps with a previously reported epitope from the Rhoptry-Associated Protein 1 and a novel epitope derived from the Rhoptry Neck Protein 5. Our approach highlights the power of combining in silico prediction with in vitro validation to discover candidate antigens that may contribute to the development of effective vaccines or immunotherapies for bovine babesiosis.
publishDate 2026
dc.date.none.fl_str_mv 2026-02-18T14:26:51Z
2026-02-18T14:26:51Z
2026-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/25222
https://www.sciencedirect.com/science/article/abs/pii/S0264410X25013799
0264-410X
1873-2518
https://doi.org/10.1016/j.vaccine.2025.128081
url http://hdl.handle.net/20.500.12123/25222
https://www.sciencedirect.com/science/article/abs/pii/S0264410X25013799
https://doi.org/10.1016/j.vaccine.2025.128081
identifier_str_mv 0264-410X
1873-2518
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv restrictedAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv Vaccine 72 : 128081. (February 2026)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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