MNAzymes and gold nanoparticles as isothermal signal amplification strategy for visual detection of miRNA
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 thei...
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Published in | Mikrochimica acta (1966) Vol. 190; no. 8; p. 292 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Vienna
Springer Vienna
01.08.2023
Springer Springer Nature B.V |
Subjects | |
Online Access | Get full text |
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Summary: | 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.
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0026-3672 1436-5073 |
DOI: | 10.1007/s00604-023-05868-y |