Journal of Nanobiotechnology (Sep 2023)

A sensitive and rapid electrochemical biosensor for sEV-miRNA detection based on domino-type localized catalytic hairpin assembly

  • Wenbin Li,
  • Wen Wang,
  • Shihua Luo,
  • Siting Chen,
  • Tingting Ji,
  • Ningcen Li,
  • Weilun Pan,
  • Xiaohe Zhang,
  • Xiaojing Wang,
  • Ke Li,
  • Ye Zhang,
  • Xiaohui Yan

DOI
https://doi.org/10.1186/s12951-023-02092-x
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 12

Abstract

Read online

Abstract Small extracellular–vesicule-associated microRNA (sEV-miRNA) is an important biomarker for cancer diagnosis. However, rapid and sensitive detection of low-abundance sEV-miRNA in clinical samples is challenging. Herein, a simple electrochemical biosensor that uses a DNA nanowire to localize catalytic hairpin assembly (CHA), also called domino-type localized catalytic hairpin assembly (DT-LCHA), has been proposed for sEV-miRNA1246 detection. The DT-LCHA offers triple amplification, (i). CHA system was localized in DNA nanowire, which shorten the distance between hairpin substrate, inducing the high collision efficiency of H1 and H2 and domino effect. Then, larger numbers of CHAs were triggered, capture probe bind DT-LCHA by exposed c sites. (ii) The DNA nanowire can load large number of electroactive substance RuHex as amplified electrochemical signal tags. (iii) multiple DT-LCHA was carried by the DNA nanowire, only one CHA was triggered, the DNA nanowire was trapped by the capture probe, which greatly improve the detection sensitivity, especially when the target concentration is extremely low. Owing to the triple signal amplification in this strategy, sEV-miRNA at a concentration of as low as 24.55 aM can be detected in 20 min with good specificity. The accuracy of the measurements was also confirmed using reverse transcription quantitative polymerase chain reaction. Furthermore, the platform showed good performance in discriminating healthy donors from patients with early gastric cancer (area under the curve [AUC]: 0.96) and was equally able to discriminate between benign gastric tumors and early cancers (AUC: 0.77). Thus, the platform has substantial potential in biosensing and clinical diagnosis. Graphical Abstract

Keywords