NLRP3, IL-1β, and caspase-1 gene transcript identification and expression by QCM-D in obese children

Modesto Gómez López, Nadia Mabel Pérez-Vielma, Haydee González Martínez, Eleazar Lara Padilla, Cindy Bandala, María Cristina González Torres, Ángel Miliar-García

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Background. Obesity in children is highly prevalent in Mexican population. Adipose tissue has been related to specific pro- and anti-inflammatory cytokine and inflammasome gene and protein expression patterns. Actually, there is no existing biosensor for detecting gene expression patterns in children with obesity. The quartz crystal microbalance with dissipation monitoring (QCM-D) has been used as a transducer for DNA biosensor design. Results. In this study, the gene expression pattern of IL-1β, NLRP3, and CASPASE-1 in children with obesity was successfully determined by means of QCM-D. Gene expression patterns were validated with those obtained by quantitative polymerase chain reaction (qPCR), a validated molecular biology technique for gene expression quantification. QCM-D analysis of the detected mass corresponding results for each of the genes showed a major detected mass for IL-1β, followed by similar NLRP3 and constitutive gene 18S deposited mass and a smaller deposited mass for CASPASE-1. Surprisingly, when comparing mRNA gene expression results for NLRP3, IL-1β, and CASPASE-1 obtained with qPCR and QCM-D, similar patterns were found, revealing greatest expression of IL-1β, followed by NLRP3, with CASPASE-1 being the molecule of least expression in the group of children with obesity. AFM images illustrate the step-by-step changes that took place on the quartz surface. Conclusions. QCM-D proved successfully for determining the gene transcripts and expression of NLRP3, IL-1β, and CASPASE-1 in children with obesity, with similar results validated by qPCR. “QCM-D decreases detection costs compared with a validated molecular biology technique.” The QCM-D biosensor developed by our group was successful for gene expression determination; in the future, it can be used for molecular diagnosis.

Original languageEnglish
Article number4323056
JournalJournal of Sensors
Volume2019
DOIs
StatePublished - 2019

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