Massively Parallel Selection of NanoCluster Beacons.
Massively Parallel Selection of NanoCluster Beacons.
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DOI：
10.1002/adma.202204957
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发表时间：
2022-10
影响因子：
29.4
通讯作者：
Yeh, Hsin-Chih
中科院分区：
文献类型：
--
作者：
Kuo, Yu-An;Jung, Cheulhee;Chen, Yu-An;Kuo, Hung-Che;Zhao, Oliver S.;Nguyen, Trung D.;Rybarski, James R.;Hong, Soonwoo;Chen, Yuan-, I;Wylie, Dennis C.;Hawkins, John A.;Walker, Jada N.;Shields, Samuel W. J.;Brodbelt, Jennifer S.;Petty, Jeffrey T.;Finkelstein, Ilya J.;Yeh, Hsin-Chih
关键词：
纳米簇信标(NCB)是一种多色银纳米簇探针，其荧光可以被称为激活剂的近端DNA链激活或调谐。虽然一对激活剂中的单核苷酸差异可以导致截然不同的激活结果，称为极性相反的双胞胎(POTS)，但使用传统的低通量表征方法很难发现新的POT-NCB。在这里，我们报告了一种高通量选择方法，该方法利用重新调整用途的下一代测序(NGS)芯片来筛选~40,000个激活序列的激活荧光。我们发现，18个核苷酸长的激活剂第7-12位碱基是产生明亮NCB的关键，第4-6位和第2-4位分别是产生黄橙色和红色花盆的热点。基于这些发现，我们提出了一个“拉链袋模型”，可以解释这些热点如何导致不同的银团簇发色团的产生，并改变发色团的化学产率。结合高通量筛选和机器学习算法，我们建立了一条在硅胶中设计色彩鲜艳的NCB的流水线。我们在重新调整用途的下一代测序芯片上筛选了约40,000个不同的纳米簇信标(NCB)，并识别出性能优于已知最佳NCB的新NCB。我们通过替换NCB中的单个核苷酸观察到了戏剧性的荧光变化，这可以用我们提出的拉链袋模型来解释。将基于芯片的高通量筛选与机器学习算法相结合，成功地设计出了色彩鲜艳、色彩鲜艳的数码相机。
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-orange and red POTs, respectively. Based on these findings, we propose a “zipper bag model” that could explain how these hotspots lead to the creation of distinct silver cluster chromophores and alter the chromophore chemical yields. Combining high-throughput screening with machine learning algorithms, we establish a pipeline to design bright and multicolor NCBs in silico. We screen ~40,000 distinct NanoCluster Beacons (NCBs) on repurposed next-generation sequencing chips and identify new NCBs that outperform the known best NCBs. We observe dramatic fluorescence changes by substituting a single nucleotide in an NCB, which could be explained by our proposed zipper-bag model. Combining the chip-based high-throughput screening with machine learning algorithms, we successfully design bright and multicolor NCBs in silico.
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DNA稳定的荧光银簇中的魔术数字导致魔术色。
DOI：
10.1021/jz500146q
发表时间：
2014-03-20
期刊：
The journal of physical chemistry letters
影响因子：
--
作者：
Copp SM;Schultz D;Swasey S;Pavlovich J;Debord M;Chiu A;Olsson K;Gwinn E
通讯作者：
Gwinn E
影响因子：
17.1
作者：
Copp, Stacy M.;Gorovits, Alexander;Gwinn, Elisabeth G.
通讯作者：
Gwinn, Elisabeth G.
影响因子：
62.1
作者：
Kobayashi, Hisataka;Ogawa, Mikako;Alford, Raphael;Choyke, Peter L.;Urano, Yasuteru
通讯作者：
Urano, Yasuteru
影响因子：
15
作者：
Chen, Yu-An;Obliosca, Judy M.;Yeh, Hsin-Chih
通讯作者：
Yeh, Hsin-Chih
影响因子：
8.6
作者：
Copp, Stacy M.;Swasey, Steven M.;Gwinn, Elisabeth G.
通讯作者：
Gwinn, Elisabeth G.