4.7 Article

Three-dimensional nanorod array for label-free surface-enhanced Raman spectroscopy analysis of microRNA pneumoconiosis biomarkers

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.saa.2021.120015

关键词

Au; ZnO; miR-19a; miR-149; miR-146a; miR-155

资金

  1. Doctoral Research Fund of Shandong Jianzhu University [X20003Z]
  2. Analysis and Support Project of Jinan Ecological Environment Bureau [GK2020-0002]
  3. Shandong Provincial Key Laboratory Project of Test Technology for Material Chemical Safety [2018SDCLHX005]

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A novel label-free surface-enhanced Raman spectroscopy (SERS) method was developed for detecting miRNA biomarkers for pneumoconiosis with a low detection limit. Density functional theory calculations and principal component analysis could accurately identify pneumoconiosis biomarkers.
Novel approaches are required to overcome the challenges associated with conventional microRNA (miRNA) detection methods and realize the early diagnosis of diseases. This work describes a novel label-free surface-enhanced Raman spectroscopy (SERS) method for the detection of the miRNA biomarkers for pneumoconiosis on a three-dimensional Au-coated ZnO nanorod array (Au-ZnO NRA). The Au-ZnO NRA substrate, which was fabricated via a modified seeding method combined with ion sputtering, provided a high enhancement factor and good spatial uniformity of the signal. With the Au-ZnO NRA, the SERS spectra of miRNAs were obtained in 30 s without labeling at room temperature. Density functional theory calculations were performed to understand the structural fingerprints of the miRNAs. Principal component analysis was carried out to identify the pneumoconiosis biomarkers based on their fingerprint SERS signals. Dual-logarithm linear relationships between the SERS intensity and the miRNA concentration were proposed for quantitative analysis. The label-free SERS method has limits of detection on the femtomolar level, which is much lower than the concentrations of the miRNA biomarkers for pneumoconiosis in lung fibroblasts. (c) 2021 Elsevier B.V. All rights reserved.

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