Natural oxidase-mimicking copper-organic frameworks for targeted identification of ascorbate in sensitive sweat sensing

Zhengyun Wang, Yuchen Huang, Kunqi Xu, Yanyu Zhong, Chaohui He, Lipei Jiang, Jiankang Sun, Zhuang Rao, Jiannan Zhu, Jing Huang, Fei Xiao, Hongfang Liu () and Bao Yu Xia ()
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Zhengyun Wang: Huazhong University of Science and Technology
Yuchen Huang: Université Paris-saclay
Kunqi Xu: Chinese Academy of Sciences
Yanyu Zhong: Huazhong University of Science and Technology
Chaohui He: Huazhong University of Science and Technology
Lipei Jiang: Huazhong University of Science and Technology
Jiankang Sun: Huazhong University of Science and Technology
Zhuang Rao: Huazhong University of Science and Technology
Jiannan Zhu: Huazhong University of Science and Technology
Jing Huang: Huazhong University of Science and Technology
Fei Xiao: Huazhong University of Science and Technology
Hongfang Liu: Huazhong University of Science and Technology
Bao Yu Xia: Huazhong University of Science and Technology

Nature Communications, 2023, vol. 14, issue 1, 1-9

Abstract: Abstract Sweat sensors play a significant role in personalized healthcare by dynamically monitoring biochemical markers to detect individual physiological status. The specific response to the target biomolecules usually depends on natural oxidase, but it is susceptible to external interference. In this work, we report tryptophan- and histidine-treated copper metal-organic frameworks (Cu-MOFs). This amino-functionalized copper-organic framework shows highly selective activity for ascorbate oxidation and can serve as an efficient ascorbate oxidase-mimicking material in sensitive sweat sensors. Experiments and calculation results elucidate that the introduced tryptophan/histidine fundamentally regulates the adsorption behaviors of biomolecules, enabling ascorbate to be selectively captured from complex sweat and further efficiently electrooxidized. This work provides not only a paradigm for specifically sweat sensing but also a significant understanding of natural oxidase-inspired MOF nanoenzymes for sensing technologies and beyond.

Date: 2023
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DOI: 10.1038/s41467-022-35721-4

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