Low-cost bacterial nanocellulose-based interdigitated biosensor to detect the p53 cancer biomarker.
BONDANCIA, Thalita Jessika; SOARES, Andrey Coatrini; POPOLIN NETO, Mário; GOMES, Nathalia Oezau; RAYMUNDO-PEREIRA, Paulo Augusto; BARUD, Hernane da Silva; MACHADO, Sergio Antonio Spinola; RIBEIRO, Sidney J L; MELENDEZ, Matias Eliseo; CARVALHO, André L.; REIS, Rui Manuel; PAULOVICH, Fernando Vieira; OLIVEIRA JUNIOR, Osvaldo Novais de.
BONDANCIA, Thalita Jessika; SOARES, Andrey Coatrini; POPOLIN NETO, Mário; GOMES, Nathalia Oezau; RAYMUNDO-PEREIRA, Paulo Augusto; BARUD, Hernane da Silva; MACHADO, Sergio Antonio Spinola; RIBEIRO, Sidney J L; MELENDEZ, Matias Eliseo; CARVALHO, André L.; REIS, Rui Manuel; PAULOVICH, Fernando Vieira; OLIVEIRA JUNIOR, Osvaldo Novais de.
Abstract: Low-cost sensors to detect cancer biomarkers with high sensitivity and selectivity are essential for early diagnosis. Herein, an immunosensor was developed to detect the cancer biomarker p53 antigen in MCF7 lysates using electrical impedance spectroscopy. Interdigitated electrodes were screen printed on bacterial nanocellulose substrates, then coated with a matrix of layer-by-layer films of chitosan and chondroitin sulfate onto which a layer of anti-p53 antibodies was adsorbed. The immunosensing performance was optimized with a 3-bilayer matrix, with detection of p53 in MCF7 cell lysates at concentrations between 0.01 and 1000 Ucell. mL-1, and detection limit of 0.16 Ucell mL-1. The effective buildup of the immunosensor on bacterial nanocellulose was confirmed with polarizationmodulated infrared reflection absorption spectroscopy (PM-IRRAS) and surface energy analysis. In spite of the high sensitivity, full selectivity with distinction of the p53-containing cell lysates and possible interferents required treating the data with a supervised machine learning approach based on decision trees. This allowed the creation of a multidimensional calibration space with 11 dimensions (frequencies used to generate decision tree rules), with which the classification of the p53-containing samples can be explained.
@article={003080779,author = {BONDANCIA, Thalita Jessika; SOARES, Andrey Coatrini; POPOLIN NETO, Mário; GOMES, Nathalia Oezau; RAYMUNDO-PEREIRA, Paulo Augusto; BARUD, Hernane da Silva; MACHADO, Sergio Antonio Spinola; RIBEIRO, Sidney J L; MELENDEZ, Matias Eliseo; CARVALHO, André L.; REIS, Rui Manuel; PAULOVICH, Fernando Vieira; OLIVEIRA JUNIOR, Osvaldo Novais de.},title={Low-cost bacterial nanocellulose-based interdigitated biosensor to detect the p53 cancer biomarker},journal={Biomaterials Advances},note={v. 134, p. 112676-1-112676-7},year={2022}}