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A Unique G-Quadruplex Aptamer: A Novel Approach for Cancer Cell Recognition, Cell Membrane Visualization, and RSV Infection Detection

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  • معلومة اضافية
    • بيانات النشر:
      MDPI AG, 2023.
    • الموضوع:
      2023
    • Collection:
      LCC:Biology (General)
      LCC:Chemistry
    • نبذة مختصرة :
      Surface staining has emerged as a rapid technique for applying external stains to trace cellular identities in diverse populations. In this study, we developed a distinctive aptamer with selective binding to cell surface nucleolin (NCL), bypassing cytoplasmic internalization. Conjugation of the aptamer with a FAM group facilitated NCL visualization on live cell surfaces with laser confocal microscopy. To validate the aptamer-NCL interaction, we employed various methods, including the surface plasmon resonance, IHC-based flow cytometry, and electrophoretic mobility shift assay. The G-quadruplex formations created by aptamers were confirmed with a nuclear magnetic resonance and an electrophoretic mobility shift assay utilizing BG4, a G-quadruplex-specific antibody. Furthermore, the aptamer exhibited discriminatory potential in distinguishing between cancerous and normal cells using flow cytometry. Notably, it functioned as a dynamic probe, allowing real-time monitoring of heightened NCL expression triggered by a respiratory syncytial virus (RSV) on normal cell surfaces. This effect was subsequently counteracted with dsRNA transfection and suppressed the NCL expression; thus, emphasizing the dynamic attributes of the probe. These collective findings highlight the robust versatility of our aptamer as a powerful tool for imaging cell surfaces, holding promising implications for cancer cell identification and the detection of RSV infections.
    • File Description:
      electronic resource
    • ISSN:
      1422-0067
      1661-6596
    • Relation:
      https://www.mdpi.com/1422-0067/24/18/14344; https://doaj.org/toc/1661-6596; https://doaj.org/toc/1422-0067
    • الرقم المعرف:
      10.3390/ijms241814344
    • الرقم المعرف:
      edsdoj.7b91ffc7210a404cbb44312361740454