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Ultrasensitive Hypoxia Sensing at the Single-Molecule Level via Super-Resolution Quantum Dot-Linked Immunosandwich Assay. | LitMetric

Ultrasensitive Hypoxia Sensing at the Single-Molecule Level via Super-Resolution Quantum Dot-Linked Immunosandwich Assay.

ACS Sens

Department of Applied Chemistry and Institute of Natural Sciences, Kyung Hee University, Yongin-si, Gyeonggi-do 17104, Republic of Korea.

Published: May 2022

Activated hypoxia-inducible factor-1alpha (HIF-1α) plays an important role in the adaptive response of tumor cells to oxygen changes through the transcriptional activation of genes that regulate important biological processes required for tumor survival and progression. In this study, we developed an ultrasensitive hypoxia sensor based on read-out with quantum dots on a gold nanodisc (quantum dot-linked immunosandwich assay, QLISA) with excellent selectivity for HIF-1α. The immunoassay platform was established by comparing the immune response results using Qdot525 as a detection nanoprobe instead of a fluorescent dye (Alexa488) (fluorescent-linked immunosandwich assay, FLISA). In addition, using three-dimensional total internal reflection fluorescence microscopy, the platform was optically sectioned along the -axis at 10 nm intervals to compare the height difference between the nanodisc and the nanoprobe following the QLISA and FLISA procedures and to localize the target location. Here, the super-resolution QLISA (srQLISA)-based hypoxia sensor exhibited high accuracy and precision for the detection of HIF-1α-extracted samples in cancer spheroids compared with the super-resolution FLISA (srFLISA) method. The developed nanobiosensor method demonstrated a wide dynamic linear detection range of 32.2 zM-8.0 pM with a limit of detection of 16 zM under optimal experimental conditions for HIF-1α, an approximate 10-fold enhanced detection sensitivity compared with the conventional enzyme-linked immunosorbent assay method based on absorbance. The detection of HIF-1α using the newly developed srQLISA sensor allows for independently predicting tumor progression and early cancer onset increases in the microvasculature density of tumor lesions.

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http://dx.doi.org/10.1021/acssensors.1c02572DOI Listing

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