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Get Free AccessOptical cross-reactive sensor arrays have recently been proven to be a powerful tool for high-throughput bioanalytes identification. Nevertheless, identification and classification of microbes, especially using microbial lysates as the analytes, still is a great challenge due to their complex composition. Herein, we achieve this goal by using luminogens featuring aggregation-induced emission characteristics (AIEgens) and graphene oxide (GO) to construct a microbial lysate responsive fluorescent sensor array. The combination of AIEgen with GO not only reduces the background signal but also induces the competition interactions among AIEgen, microbial lysates, and GO, which highly improves the discrimination ability of the sensor array. As a result, six microbes, including two fungi, two Gram-positive bacteria, and two Gram-negative bacteria are precisely identified. Thus, this work provides a new way to design safer and simpler sensor arrays for the discrimination of complex analytes.
Jianlei Shen, Rong Hu, Taotao Zhou, Zhiming Wang, Yiru Zhang, Shiwu Li, Gui Chen, Meijuan Jiang, Anjun Qin, Ben Zhong Tang (2018). Fluorescent Sensor Array for Highly Efficient Microbial Lysate Identification through Competitive Interactions. , 3(11), DOI: https://doi.org/10.1021/acssensors.8b00650.
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Type
Article
Year
2018
Authors
10
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1021/acssensors.8b00650
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