Decoding ubiquitination in the fight against malaria: a network-based exploration of E1-E2-E3 enzyme triples in Plasmodium falciparum

• Ano de defesa: 2023
• Autor(a) principal: Cano, Lyang Higa
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Correspondência E1-E2-E3; E1-E2-E3 matching; Gene co-expression network; Malaria; Malária; Plasmodium falciparum; Rede de co-expressão gênica; Ubiquitinação; Ubiquitination
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/95/95131/tde-09012024-171914/

Plasmodium falciparum is the causative agent of malaria, a disease responsible for a significant number of global deaths. Decades of integrative research, encompassing genomics, transcriptomics, cell biology, and host interactions, have been dedicated to combating this parasite. As an eukaryotic intracellular pathogen, P. falciparum regulates its protein activity through the ubiquitin-proteasome system (UPS), orchestrating essential cellular processes. The UPS pathway operates through a three-step enzymatic cascade involving three distinct groups: E1, E2, and E3 enzymes. An intricate puzzle lies in the identification of enzyme triples (E1, E2, E3) that collaborate within the same chain reaction during the intraerythrocytic developmental cycle (IDC) in P. falciparum. This quest is significant given the incomplete understanding of this phenomenon and its potential impact on malaria control. To address this problem, we propose an innovative approacha Gene Co-expression Network (GCN) model for the systematic ranking of enzyme triples (E1, E2, E3). This model, based on the concept that co-expressed genes are likely involved in the same biological processes, provides an avenue to identify triples operating in tandem. The model\'s efficacy was tested across seven temporal RNA-Seq transcriptome datasets, each representing distinct experimental conditions and temporal stages during the IDC. Remarkably, our model revealed three triples (E1, E2, E3) that consistently collaborated across all seven datasets, demonstrating remarkable stability amidst varying experimental contexts. This research not only enhances our comprehension of the UPS pathway in P. falciparum but also sheds light on potential targets for combating malaria. By deciphering the Ubiquitin Code, we aim to unravel the mechanisms underpinning critical biological processes, ultimately contributing to the global battle against malaria.