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

2022; American Chemical Society; Volume: 13; Issue: 22 Linguagem: Inglês

10.1021/acs.jpclett.2c01252

1948-7185

Grace A. DeSalvo, Grayson R. Hoy, Isabelle M. Kogan, John Z. Li, Elise T. Palmer, Emilio Luz‐Ricca, Paul Scemama de Gialluly, Kristin L. Wustholz,

Biosensors and Analytical Detection

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.