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Development and implementation of a BoLA-null cell system for immunopeptidomics characterisation of BoLA-DR ligands and production of a catalogue of predicted ligands from tick sialotranscriptomes for anti-tick vaccine development

Grant number: 22/02776-5
Support Opportunities:Scholarships abroad - Research Internship - Post-doctor
Effective date (Start): September 01, 2022
Effective date (End): August 25, 2023
Field of knowledge:Biological Sciences - Parasitology
Principal Investigator:Beatriz Rossetti Ferreira
Grantee:Andressa Fisch
Supervisor: Timothy Connelley
Host Institution: Escola de Enfermagem de Ribeirão Preto (EERP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
Research place: University of Edinburgh, Scotland  
Associated to the scholarship:18/23579-8 - Development of a recombinant multicomponent chimeric vaccine based in protein epitopes from Rhipicephalus microplus ticks, BP.PD


Ticks are important vectors of diseases to animals and promote significant losses in the cattle production sector. The vaccines currently available against ticks show variable outcomes of protection between bovines and little lasting memory immune response, indicating the need to develop more efficient vaccines. It is widely known that CD4 T cell signalling is essential for developing effective antibody responses against pathogens and that MHCII presentation is a mandatory step for cell activation. Recently, the characterisation of MHCII ligands by immunopeptidomics helped the development 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. In this project, we propose to produce a bovine-derived BoLA-null cell line through CRISPR/Cas9 system that will be used as a platform to express selected BoLA molecules and generate mono-allelic samples for immunopeptidodme characterisation. This platform will be used to express the BoLA-DRB3 alleles mostly prevalent in commercial cattle breeds in Brazil, specifically Nelore (beef cattle) and Girolando (milk cattle) and to perform immunopeptidomics analysis that will help to depict the binding motifs of these alleles. The binding motifs so defined will be used to expand the BoLAII ligand prediction tool NetBoLAIIpan, previously constructed by our group and freely available at NetBoLAIIpan. Lastly, we will perform a high-throughput ligand prediction on a dataset comprised of ~3600 proteins derived from the sialotranscriptome of Rhipicephalus microplus ticks, previously characterised by our research group, to generate an easy-to-read catalogue of potential antigens and predicted ligands for each analysed BoLA-DR allele. This catalogue will reduce the costs and time required to provide bioinformatics support for the rational screening of tick antigens and epitopes for anti-tick vaccine development. (AU)

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