Blinking-Based Multiplexing: A New Approach for Differentiating Spectrally Overlapped Emitters.

Autor:	DeSalvo GA; Department of Chemistry, William & Mary, P.O. Box 8795, Williamsburg, Virginia 23187, United States., Hoy GR; Department of Chemistry, William & Mary, P.O. Box 8795, Williamsburg, Virginia 23187, United States., Kogan IM; Department of Chemistry, William & Mary, P.O. Box 8795, Williamsburg, Virginia 23187, United States., Li JZ; Department of Chemistry, William & Mary, P.O. Box 8795, Williamsburg, Virginia 23187, United States., Palmer ET; Department of Chemistry, William & Mary, P.O. Box 8795, Williamsburg, Virginia 23187, United States., Luz-Ricca E; Department of Chemistry, William & Mary, P.O. Box 8795, Williamsburg, Virginia 23187, United States., de Gialluly PS; Department of Chemistry, William & Mary, P.O. Box 8795, Williamsburg, Virginia 23187, United States., Wustholz KL; Department of Chemistry, William & Mary, P.O. Box 8795, Williamsburg, Virginia 23187, United States.
Jazyk:	angličtina
Zdroj:	The journal of physical chemistry letters [J Phys Chem Lett] 2022 Jun 09; Vol. 13 (22), pp. 5056-5060. Date of Electronic Publication: 2022 Jun 02.
DOI:	10.1021/acs.jpclett.2c01252
Abstrakt:	Multicolor single-molecule imaging is widely applied to answer questions in biology and materials science. However, most studies rely on spectrally distinct fluorescent probes or time-intensive sequential imaging strategies to multiplex. Here, we introduce blinking-based multiplexing (BBM), a simple approach to differentiate spectrally overlapped emitters based solely on their intrinsic blinking dynamics. The blinking dynamics of hundreds of rhodamine 6G and CdSe/ZnS quantum dots on glass are obtained using the same acquisition settings and analyzed with a change point detection algorithm. Although substantial blinking heterogeneity is observed, the analysis yields a blinking metric with 93.5% classification accuracy. We further show that BBM with up to 96.6% accuracy is achieved by using a deep learning algorithm for classification. This proof-of-concept study demonstrates that a single emitter can be accurately classified based on its intrinsic blinking dynamics and without the need to probe its spectral color.
Databáze:	MEDLINE
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