Identificação, caracterização e aplicação biotecnológica de uma serino-peptidase da planta carnívora Nepenthes mirabilis para hidrólise das proteínas do leite bovino

• Ano de defesa: 2020
• Autor(a) principal: Nascimento, Camila Tauane Monteiro do
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Escherichia coli; Alergia alimentar; Expressão heteróloga; Corpos de inclusão; Peptidase
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/51901

Bovine milk proteins are responsible by the most common type of food allergy. People diagnosed with milk allergy use formulas containing partially or extensively hydrolyzed milk proteins. Because these formulas are costy, due to enzymatic process, the research for new proteases, able to more efficiently produce hypoallergenic formulas, is still an exciting subject. This work aimed to evaluate the biotechnological potential for the hydrolysis of bovine milk proteins and to characterize three serine carboxyproteases (SCP) of the digestive fluid of the Nepenthes mirabilis carnivorous plant (SCP3, SCP20, and SCP47). Besides, a protease (SCP3) was chosen for further heterologous expression in Escherichia coli Shuffle®T7. SDS-PAGE showed that SCP extensively hydrolyzed bovine caseins, resulting in a lower antigenicity of the hydrolysates, measured by ELISA, when compared to non-hydrolyzed bovine caseins. In silico analyzes of the three SCP revealed similarities of primary, secondary, and three-dimensional structures with other plant SCP, being classified as belonging to the SC clan of the serine proteases. Although SCP3 was obtained in its soluble form using 1% ethanol during induction with 0.5 mM IPTG at 16 oC for 18 h, it did not show proteolytic activity. Obtaining of this protein in its active form can lead to its application in the food industry for the hydrolysis of cow's milk proteins with the production of hypoallergenic formulas, because SCP3 also showed low allergenic potential and it was extensively hydrolyzed by digestive proteases, both predicted using bioinformatics tools.