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Development of a BoLA-null cell platform using the CRISPR/Cas9 system for immunopeptidomic characterization of BoLA-DR ligands

Grant number: 23/04771-3
Support Opportunities:Regular Research Grants
Duration: November 01, 2023 - October 31, 2025
Field of knowledge:Biological Sciences - Immunology - Applied Immunology
Principal Investigator:Beatriz Rossetti Ferreira
Grantee:Beatriz Rossetti Ferreira
Host Institution: Escola de Enfermagem de Ribeirão Preto (EERP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
Associated researchers: Timothy Connelley

Abstract

Ticks are complex parasites and the most relevant vectors of potentially lethal diseases to bovines, promoting significant losses in the cattle-raising sector. The anti-tick vaccines currently available induce specific antibody responses, but show variable outcomes of protection between animals and short-lived immune responses, indicating the need to develop more efficient vaccines. CD4 T cell signaling mediated by the TCR recognition of MHCII-bound peptides is a mandatory step for B cell activation and maturation in antibody secreting-cells, and is essential for developing effective antibody responses against pathogens. Recently, the characterization of MHC II ligands by immunopeptidomics greatly improved the development and accuracy of MHC-binding prediction algorithms. Such in silico tools accelerated the rational selection of antigens and epitopes for vaccine development, especially for vaccines against pathogens with large proteomes, like ticks. Our group has developed a bovine-dedicated BoLA-DRB3 ligand prediction tool, NetBoLAIIpan, using immunopeptidomic data; however, the cell models previously used were not optimized and could not be transferred to our Lab in Brazil due to biosafety limitations, preventing further experiments to expand ligand database and anti-tick research. Thus, we propose to produce a bovine-derived "BoLA-null" cellular platform, with impaired expression of endogenous MHC, and validate its capacity to express targeted BoLA-DR alleles and provide reliable immunopeptidomic datasets. MDBK cells will be submitted to MHC knockout using CRISPR/Cas9 system, and the MHC-negative cells will be used as host for expression of reference BoLA-DRB3 alleles by plasmid transfection. Immunopeptidomic data generated by MS/MS will be used for training of test ligand prediction algorithms, then compared with the reference tool NetBoLAIIpan to define quality of data. If successful, this platform will overcome the limitations of the previous model, and will allow further research to characterize the ligand motifs from BoLA-DRB3 alleles prevalent in commercial cattle breeds in Brazil. This may well assist the expansion of the dataset of the NetBoLAIIpan tool and high-coverage ligand prediction on tick sialotrasncriptomes, while reduce the costs and time required to provide the bioinformatics support for the rational screening of tick antigens and epitopes for anti-tick vaccine development. (AU)

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