Desenvolvimento de uma ferramenta para análise de dados de sequenciamento NGS de bibliotecas de scFvs selecionados por phage display

Detalhes bibliográficos
Ano de defesa: 2023
Autor(a) principal: Batista, Mathias Coelho
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
NGS
Link de acesso: http://www.repositorio.ufc.br/handle/riufc/71372
Resumo: Monoclonal antibodies (mAbs) are globular proteins capable of recognizing, binding and eliciting an immune response against specific molecular targets, being widely applied in the treatment of various diseases. Among the techniques that can be applied in the development of mAbs, phage display stands out for its ability to select mAb fragments capable of binding to a specific target. When associated with next-generation sequencing (NGS) technologies, phage display becomes a powerful tool because it allows precise tracking of which and how each fragment was selected. ATTILA is a computational pipeline capable of identifying which candidates were most enriched during selection, through the analysis of data from NGS sequencing of phage display libraries. Although efficient in performing this function, ATTILA has a unfriendly installation, configuration, and usage processes, and is unable to fully utilize available computational power. Therefore, this project aims to develop a computational tool based on ATTILA with better performance, usability, and new functions. The development resulted in a new tool (ATTILA 2.0) that includes a graphical interface for input parameter insertion and result visualization, optimized processing for better use of computational resources, and a restructured analysis process to enable simultaneous analysis of multiple rounds and execution of part of the processing through cloud computing. In addition, a single installer was created to facilitate and speed up the installation process, and the tool was validated. ATTILA 2.0 is more user-friendly, both due to the existence of a graphical interface and the facilitation of installation by the installer. Through the implementation of multiprocessing, ATTILA 2.0 was shown to better utilize available computational resources. The code restructuring allowed for the analysis of libraries obtained from NGS sequencing of multiple rounds of phage display selection, as well as the division of processing between the user’s machine and an API hosted on a Fiocruz server, and the feeding of a database that will allow future integrations with other tools. Validation was performed through the analysis of NGS data from the sequencing of phage display selection libraries targeting one of the loops of the CD20 protein.