RT Journal Article
SR Electronic
T1 Massively Parallel Selection of NanoCluster Beacons
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.12.04.471212
DO 10.1101/2021.12.04.471212
A1 Yu-An Kuo
A1 Cheulhee Jung
A1 Yu-An Chen
A1 Hung-Che Kuo
A1 Oliver S. Zhao
A1 Trung D. Nguyen
A1 James R. Rybarski
A1 Soonwoo Hong
A1 Yuan-I Chen
A1 Dennis C. Wylie
A1 John A. Hawkins
A1 Jada N. Walker
A1 Samuel W. Shields
A1 Jennifer S. Brodbelt
A1 Jeffrey T. Petty
A1 Ilya J. Finkelstein
A1 Hsin-Chih Yeh
YR 2021
UL http://biorxiv.org/content/early/2021/12/05/2021.12.04.471212.abstract
AB NanoCluster Beacons (NCBs) are multicolor silver nanocluster probes whose fluorescence can be activated or tuned by a proximal DNA strand called the activator. While a single-nucleotide difference in a pair of activators can lead to drastically different activation outcomes, termed the polar opposite twins (POTs), it is difficult to discover new POT-NCBs using the conventional low-throughput characterization approaches. Here we report a high-throughput selection method that takes advantage of repurposed next-generation-sequencing (NGS) chips to screen the activation fluorescence of ∼40,000 activator sequences. We find the nucleobases at positions 7-12 of the 18-nucleotide-long activator are critical to creating bright NCBs and positions 4-6 and 2-4 are hotspots to generate yellow and red POTs, respectively. Based on these findings, we propose a “zipper bag model” that explains how these hotspots lead to the creation of distinct silver cluster chromophores and contribute to the difference in chromophore chemical yields. Combining high-throughput screening with machine learning algorithms, we establish a pipeline to rationally design bright and multicolor NCBs.Competing Interest StatementThe authors have declared no competing interest.