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Published July 2023 | Version v1
Journal article

MNAzymes and gold nanoparticles as isothermal signal amplification strategy for visual detection of miRNA

  • 1. Department of Physical and Analytical Chemistry, University of Oviedo, Oviedo (Spain)
  • 2. Health Research Institute of Asturias, ISPA, Avenida Hospital Universitario, Oviedo (Spain)
  • 3. Department of Functional Biology, Genetics, University of Oviedo, Oviedo (Spain)
  • 4. Department of Electrical, Electronic, Communications and Systems Engineering, University of Oviedo, Gijón (Spain)

Description

MicroRNAs (miRNAs) represent a class of small noncoding RNAs that are considered a novel emerging class of disease biomarkers in a variety of afflictions. Sensitive detection of miRNA is typically achieved using hybridization-based methods coupled with genetic amplification techniques. Although their sensitivity has improved, amplification techniques often present erroneous results due to their complexity. In addition, the use of these techniques is usually linked to the application of protein enzymes, the activity of which is dependent on the temperature and pH of the medium. To address these drawbacks, an alternative genetic enzyme for the highly sensitive detection of miRNAs is proposed in this work. Multicomponent nucleic acid enzymes (MNAzymes), coupled with the use of DNA-functionalized gold nanoparticles (AuNPs), were used in this study to develop an isothermal signal amplification strategy for visual genetic detection. miR146a, a biomarker of bovine mastitis present in milk, was selected as a model analyte. The developed methodology is easily carried out in 80 min at 50 °C, generating a low visual limit of detection of 250 pM based on the observation of a color change. The methodology was successfully applied to the detection of miR146a in raw cow milk samples. Graphical

Additional details

Publishing Information

Journal Title
Microchimica Acta (Online)
Journal Volume
190
Journal Issue
8
Journal Page Range
p. 1-11
ISSN
1436-5073

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Copyright
Copyright (c) 2023 The Author(s)