4.8 Article

Hydrogel-Embedded Quantum Dot-Transcription Factor Sensors for Quantitative Progesterone Detection

期刊

ACS APPLIED MATERIALS & INTERFACES
卷 12, 期 39, 页码 43513-43521

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acsami.0c13489

关键词

biosensing; quantum dots; transcription factor; hydrogel; Forster resonance energy transfer

资金

  1. NIH [U54EB015403, R01GM129437, 1KL2TR001411]
  2. DARPA [W911NF-16-C-0044]
  3. BU Kilachand
  4. BME distinguished fellowship
  5. BUnano Terrier Tank award
  6. Clare Booth Luce Graduate Fellowship
  7. European Union under the program H2020 [749973]
  8. Boston University Micro and Nano Imaging Facility
  9. Boston University Precision Diagnostics Center
  10. Office of the Director, National Institutes of Health [S10OD024993]
  11. Marie Curie Actions (MSCA) [749973] Funding Source: Marie Curie Actions (MSCA)

向作者/读者索取更多资源

Immobilization of biosensors in or on a functional material is critical for subsequent device development and translation to wearable technology. Here, we present the development and assessment of an immobilized quantum dot-transcription factor-nucleic acid complex for progesterone detection as a first step toward such device integration. The sensor, composed of a polyhistidine-tagged transcription factor linked to a quantum dot and a fluorophore-modified cognate DNA, is embedded within a hydrogel as an immobilization matrix. The hydrogel is optically transparent, soft, and flexible as well as traps the quantum dot-transcription factor DNA assembly but allows free passage of the analyte, progesterone. Upon progesterone exposure, DNA dissociates from the quantum dot-transcription factor DNA assembly resulting in an attenuated ratiometric fluorescence output via Forster resonance energy transfer. The sensor performs in a dose-dependent manner with a limit of detection of 55 nM. Repeated analyte measurements are similarly successful. Our approach combines a systematically characterized hydrogel as an immobilization matrix and a transcription factor-DNA assembly as a recognition/transduction element, offering a promising framework for future biosensor devices.

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