A detection and quantification label-free tool to speed up downstream processing of model mucins

• Autor(a) principal: Carvalho, Sofia B.
• Data de Publicação: 2018
• Outros Autores: Moreira, Ana Sofia, Gomes, Joana, Carrondo, Manuel J.T., Thornton, David J., Alves, Paula M., Costa, Julia, Peixoto, Cristina
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://doi.org/10.1371/journal.pone.0190974
• topic: Biochemistry, Genetics and Molecular Biology(all); Agricultural and Biological Sciences(all); SDG 3 - Good Health and Well-being

Mucins are high-molecular weight glycoproteins (0.25–20 MDa) containing one or more domains that are heavily O-glycosylated. Their implications as targets for cancer treatment have increased the interest in these glycoproteins, mainly in the fields of vaccines and antibodies. However, mucins present high heterogeneity, posing challenges that affect purification processes and quality control analysis. In that sense, it is necessary to develop and improve downstream processes and analytical methods to characterize these products. Here a tool based on biolayer interferometry analysis to improve mucin’s detection and quantification in a fast, simple and label free-way is presented. Taking advantage of lectin recognition of mucins’ carbohydrate structures, several lectins were evaluated and immobilized on streptavidin biosensors. Different assay conditions were optimized and the most suitable lectin, Aleuria aurantia lectin (AAL), was selected. Bovine Submaxillary Gland and human MUC5B mucins were used as proof of concept and were successfully detected and quantified at different stages of purification. High sensitivity levels were achieved with LOD and LOQ of 3.8 μg mL-1 and 11.7 μg mL-1 for BSM, and 0.2 μg mL-1 and 0.6 μg mL-1 for MUC5B. AAL binding specificity was also confirmed with fucose competition assays. Our method represents an advance on mucins detection and quantification since the existing methods present several disadvantages for process development. Hereafter, it can be applied to the optimization of new or already established downstream processes for mucins’ purification.